We present the implementation of a spectral kurtosis based Radio-Frequency Interference detection system on the CHIME instrument and its reduced-scale pathfinder. Our implementation extends single-receiver formulations to the case of a compact array, combining samples from multiple receivers to improve the confidence with which RFI is detected. Through comparison between on-sky data and simulations, we show that the statistical properties of the canonical spectral kurtosis estimator are functionally unchanged by cross-array integration. Moreover, by comparison of simultaneous data from CHIME and the Pathfinder, we evaluate our implementation's capacity for interference discrimination for compact arrays of various size. We conclude that a spectral kurtosis based implementation provides a scalable, high cadence RFI discriminator for compact multi-receiver arrays.

We have developed a digital readout system for radiographic images using a scanning laser beam. In this system, electrostatic charge images on amorphous selenium (alpha-Se) plates are read out using photo-induced discharge (PID). We discuss the design requirements of a laser scanner for the PID system and describe its construction from commercially available components. The principles demonstrated can be adapted to a variety of digital imaging systems.

IntroductionEmotional awareness is the ability to identify, interpret, and verbalize the emotional responses of oneself and those of others. The Levels of Emotional Awareness Scale (LEAS) is an objective performance inventory that accurately measures an individual's emotional awareness. LEAS assessments are typically scored manually and are therefore both time consuming and cognitively demanding. This study presents a German electronic scoring program for the LEAS (geLEAS), the first non-English computerized assessment approach of the LEAS.MethodsData were collected from a healthy German community sample (N = 208). We developed a modern software for computerizing LEAS scoring, an open-source text-based emotion assessment tool called VETA (Verbal Emotion in Text Assessment). We investigated if the software would arrive at similar results as hand scoring in German and if emotional awareness would show similar associations to sociodemographic information and psychometric test results as in previous studies.ResultsThe most frequently used scoring method of the geLEAS shows excellent internal consistency (α = 0.94) and high correlations with hand scoring (r = 0.97, p < 0.001). Higher emotional awareness measured by the geLEAS is associated with female gender, older age, and higher academic achievement (all p < 0.001). Moreover, it is linked to the ability to identify emotions in facial expressions (p < 0.001) and more accurate theory of mind functioning (p < 0.001).DiscussionAn automated method for evaluating emotional awareness greatly expands the ability to study emotional awareness in clinical care and research. This study aims to advance the use of emotional awareness as a clinical and scientific parameter.